Abstract:Fig. 1. a) Marijuana Craving Questionnaire Short Form (MCQ-SF) Total Score, recorded prior to each of the denoted treatment visits; and 1b) Average number of cannabis use sessions per day as measured by the Time Line Follow-back (TLFB).
“…A case series ( N = 3) suggested that rTMS directed to bilateral DLPFC for 20 sessions may reduced cannabis use and craving, with a large effect size (Cohen’s d = 1.2) 42 . Since these effects of rTMS may be mediated by targeting specific brain circuits 35 , it was critical to evaluate cannabis craving/withdrawal symptoms.…”
Section: Discussionmentioning
confidence: 99%
“…No significant changes in craving were found between active and sham groups. Recently, this group completed an open-label safety trial applying 20-sessions (10-Hz) to DLPFC over 2 weeks to nine individuals with CUD; only three completed the trial 42 . Thus, further research is warranted.…”
Cannabis use disorder (CUD) occurs at high rates in schizophrenia, which negatively impacts its clinical prognosis. These patients have greater difficulty quitting cannabis which may reflect putative deficits in the dorsolateral prefrontal cortex (DLPFC), a potential target for treatment development. We examined the effects of active versus sham high-frequency (20-Hz) repetitive transcranial magnetic stimulation (rTMS) on cannabis use in outpatients with schizophrenia and CUD. Secondary outcomes included cannabis craving/withdrawal, psychiatric symptoms, cognition and tobacco use. Twenty-four outpatients with schizophrenia and CUD were enrolled in a preliminary double-blind, sham-controlled randomized trial. Nineteen participants were randomized to receive active (n = 9) or sham (n = 10) rTMS (20-Hz) applied bilaterally to the DLPFC 5x/week for 4 weeks. Cannabis use was monitored twice weekly. A cognitive battery was administered pre- and post-treatment. rTMS was safe and well-tolerated with high treatment retention (~90%). Contrast estimates suggested greater reduction in self-reported cannabis use (measured in grams/day) in the active versus sham group (Estimate = 0.33, p = 0.21; Cohen’s d = 0.72), suggesting a clinically relevant effect of rTMS. A trend toward greater reduction in craving (Estimate = 3.92, p = 0.06), and significant reductions in PANSS positive (Estimate = 2.42, p = 0.02) and total (Estimate = 5.03, p = 0.02) symptom scores were found in the active versus sham group. Active rTMS also improved attention (Estimate = 6.58, p < 0.05), and suppressed increased tobacco use that was associated with cannabis reductions (Treatment x Time: p = 0.01). Our preliminary findings suggest that rTMS to the DLPFC is safe and potentially efficacious for treating CUD in schizophrenia.
“…A case series ( N = 3) suggested that rTMS directed to bilateral DLPFC for 20 sessions may reduced cannabis use and craving, with a large effect size (Cohen’s d = 1.2) 42 . Since these effects of rTMS may be mediated by targeting specific brain circuits 35 , it was critical to evaluate cannabis craving/withdrawal symptoms.…”
Section: Discussionmentioning
confidence: 99%
“…No significant changes in craving were found between active and sham groups. Recently, this group completed an open-label safety trial applying 20-sessions (10-Hz) to DLPFC over 2 weeks to nine individuals with CUD; only three completed the trial 42 . Thus, further research is warranted.…”
Cannabis use disorder (CUD) occurs at high rates in schizophrenia, which negatively impacts its clinical prognosis. These patients have greater difficulty quitting cannabis which may reflect putative deficits in the dorsolateral prefrontal cortex (DLPFC), a potential target for treatment development. We examined the effects of active versus sham high-frequency (20-Hz) repetitive transcranial magnetic stimulation (rTMS) on cannabis use in outpatients with schizophrenia and CUD. Secondary outcomes included cannabis craving/withdrawal, psychiatric symptoms, cognition and tobacco use. Twenty-four outpatients with schizophrenia and CUD were enrolled in a preliminary double-blind, sham-controlled randomized trial. Nineteen participants were randomized to receive active (n = 9) or sham (n = 10) rTMS (20-Hz) applied bilaterally to the DLPFC 5x/week for 4 weeks. Cannabis use was monitored twice weekly. A cognitive battery was administered pre- and post-treatment. rTMS was safe and well-tolerated with high treatment retention (~90%). Contrast estimates suggested greater reduction in self-reported cannabis use (measured in grams/day) in the active versus sham group (Estimate = 0.33, p = 0.21; Cohen’s d = 0.72), suggesting a clinically relevant effect of rTMS. A trend toward greater reduction in craving (Estimate = 3.92, p = 0.06), and significant reductions in PANSS positive (Estimate = 2.42, p = 0.02) and total (Estimate = 5.03, p = 0.02) symptom scores were found in the active versus sham group. Active rTMS also improved attention (Estimate = 6.58, p < 0.05), and suppressed increased tobacco use that was associated with cannabis reductions (Treatment x Time: p = 0.01). Our preliminary findings suggest that rTMS to the DLPFC is safe and potentially efficacious for treating CUD in schizophrenia.
“…The following sections briefly introduce behavioral and pharmacologic strategies that may facilitate neurobiobehavioral recovery and improve long-term outcomes. 2 Other approaches, including neuromodulation, are gaining momentum as possible interventions for substance use disorders 58 but will not be discussed.…”
Alcohol use disorder (AUD) commonly is associated with compromise in neurobiological and/or neurobehavioral processes. The severity of this compromise varies across individuals and outcomes, as does the degree to which recovery of function is achieved. This narrative review first summarizes neurobehavioral, neurophysiological, structural, and neurochemical aberrations/deficits that are frequently observed in people with AUD after detoxification. Subsequent sections review improvements across these domains during recovery, taking into account modulators of recovery to the extent permitted. Where appropriate, the discussion includes work integrating outcomes across domains, leveraging the strengths of diverse experimental methods. Interventions to ameliorate neurobiological or neurobehavioral deficits do not constitute a primary objective of this review. However, their consideration is a logical inclusion. Therefore, a limited introduction to existing methods is also presented.
“…So, there is an urgent need to identify and develop novel therapeutic interventions for CUD. Recent advancements in human neuroscience have provided new adjuvant treatment options including noninvasive brain stimulation (NIBS) interventions for those individuals with CUD who desire to quit substance abuse based on targeting the neurocognitive processes (Kearney-Ramos & Haney, 2021;Sahlem et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…In substance use disorders (SUDs), it has been reported that activity in the prefrontal cortex and its connectivity to the subcortical regions (including striatum and amygdala) that are related to addictive behaviors such as drug craving can be modulated by NIBS methods (Jansen et al, 2013;Ma, Sun, & Ku, 2019). Research on repetitive transcranial magnetic stimulation (rTMS) for the treatment of CUD showed encouraging results for enhancing drug craving or consumption (Kearney-Ramos & Haney, 2021;Martin-Rodriguez et al, 2021;Prashad, Dedrick, To, Vanneste, & Filbey, 2019;Sahlem, Baker, George, Malcolm, & McRae-Clark, 2018;Sahlem et al, 2020).…”
Introduction: Transcranial direct current stimulation (tDCS) has been studied as an adjunctive treatment option for substance use disorders (SUDs). Alterations in brain structure following SUD may change tDCS-induced electric field (EF) and subsequent responses. However, group-level differences between healthy controls (HC) and participants with SUDs in terms of EF and its association with cortical architecture have not yet been modeled quantitatively. Objective: We provided a methodology for group-level analysis of computational head models (CHMs) to investigate the influence of cortical morphology metrics on EFs. Method: Whole-brain surface-based morphology was conducted and cortical thickness, volume, and surface area were compared between participants with CUD (n=20) and age-matched HC (n=22). We also simulated EFs for bilateral tDCS over DLPFC. Effects of structural alterations on EF distribution were investigated based on individualized CHMs. Results: In terms of EF, no significant difference was found within the prefrontal cortex. However, EFs were significantly different in left-postcentral and right-superior temporal gyrus (P < 0.05) with higher level of variance in CUD compared to HC (F39,43=5.31,P<0.0001,C =0.95). We found significant differences in cortical area (caudal anterior cingulate and rostral middle frontal), thickness (lateral orbitofrontal), and volume (paracentral and fusiform) between two groups. Conclusion: Brain morphology and tDCS-induced EFs may be changed following CUD. However, differences between CUD and HCs in EFs do not always overlap with brain areas that showed structural alterations. To sufficiently modulate stimulation targets, it should be checked if individuals with CUD need to be given different stimulation dose based on tDCS target location.
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